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Understanding the Importance of Using Patient-Reported Outcome Measures in Patients With Immune Thrombocytopenia

2013· article· en· W2144640698 on OpenAlex
Monika Kirsch, Robert J. Klaassen, Sabina De Geest, Axel Matzdorff, Tatyana Ionova, Fabienne Dobbels

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSeminars in Hematology · 2013
Typearticle
Languageen
FieldMedicine
TopicPlatelet Disorders and Treatments
Canadian institutionsUniversity of OttawaChildren's Hospital of Eastern Ontario
Fundersnot available
KeywordsImmune thrombocytopeniaMedicineIntensive care medicinePatient-reported outcomeClinical PracticeDiseasePlateletQuality of life (healthcare)ImmunologyFamily medicineInternal medicine

Abstract

fetched live from OpenAlex

Incorporating patient-reported outcomes (PROs) when studying patients with immune thrombocytopenia (ITP) is essential since treatment decisions are complex and using platelet count only partly explains disease burden. Since most symptoms are only experienced subjectively and are seldom captured during clinician-based evaluations, using self-report is crucial for early symptom detection. However, capturing the patient's illness experience necessitates using well-developed and validated instruments. This article provides insight on the importance of using PROs in ITP, summarizes the methodological steps to develop PRO instruments, and discusses challenges related to integrating PROs into research and clinical practice.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.374

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.067
GPT teacher head0.292
Teacher spread0.225 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it